Patents by Inventor Junwei Pan
Junwei Pan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240140699Abstract: The present invention discloses a container equipment for enclosed transportation and heterotopic and aerobic stabilization of reserved garbage, which includes a container body and a functional lining provided on an inner wall of the container body, wherein the functional lining is provided with a circulating air low-temperature evaporation system, a water distribution and drainage system and a heating and insulating system; the circulating air low-temperature evaporation system includes an air inlet manifold, an air distribution perforated pipe, a base plate water discharge and air distribution groove and a top plate water distribution and air guide groove, an air extraction perforated pipe, a fan, an air outlet pipe and a quicklime dehydration and deodorization system; the water distribution and drainage system includes a percolate feeding pipe, a fiber capillary water distribution pipe, the top plate water distribution and air guide groove, a side drain, a main drain and a percolate discharge pipe; the heaType: ApplicationFiled: April 28, 2022Publication date: May 2, 2024Inventors: Jun WU, Yifan CHEN, Zhouzhi PAN, YiIian LV, Haitao MA, Junwei ZHU, ZhiIi YANG, Pinghai Li, Wangfeng XUE
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Patent number: 11941669Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: April 24, 2023Date of Patent: March 26, 2024Assignee: Yahoo Ad Tech LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20230334530Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: June 26, 2023Publication date: October 19, 2023Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20230316337Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: April 24, 2023Publication date: October 5, 2023Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20230289662Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: ApplicationFiled: May 21, 2023Publication date: September 14, 2023Inventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Guitekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron Flores
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Publication number: 20230281512Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: ApplicationFiled: May 15, 2023Publication date: September 7, 2023Inventors: Tian Zhou, Djoefje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Patent number: 11687978Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: GrantFiled: May 23, 2022Date of Patent: June 27, 2023Assignee: Yahoo Assets LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11657326Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: GrantFiled: August 17, 2020Date of Patent: May 23, 2023Assignee: YAHOO AD TECH LLCInventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Gultekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron Flores
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Patent number: 11651284Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: GrantFiled: August 17, 2020Date of Patent: May 16, 2023Assignee: YAHOO AD TECH LLCInventors: Tian Zhou, Djordje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan Kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Patent number: 11636521Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: March 9, 2022Date of Patent: April 25, 2023Assignee: YAHOO AD TECH LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20230108682Abstract: A data processing method includes: acquiring a first intersection set, acquiring a second intersection set, calculating an intersection between the first intersection set and the second intersection set to obtain an intersection result set that includes an intersecting portion of the first intersection data and the second intersection data, and obfuscating the intersection result set to obtain an obfuscation set that includes obfuscated data based on data in the second intersection set and an intersection data set based on the intersection result set.Type: ApplicationFiled: November 30, 2022Publication date: April 6, 2023Applicant: Tencent Technology (Shenzhen) Company LimitedInventors: Fangcheng FU, Jie JIANG, Junwei PAN, Chen HOU, Huanran XUE, Yong CHENG, Yuhong LIU, Peng CHEN, Yangyu TAO
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Publication number: 20220277354Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: May 23, 2022Publication date: September 1, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220198526Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: March 9, 2022Publication date: June 23, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11341541Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: GrantFiled: September 22, 2020Date of Patent: May 24, 2022Assignee: YAHOO ASSETS LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11295346Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: September 22, 2020Date of Patent: April 5, 2022Assignee: VERIZON MEDIA INC.Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220092645Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: September 22, 2020Publication date: March 24, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220092644Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: September 22, 2020Publication date: March 24, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220051130Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: ApplicationFiled: August 17, 2020Publication date: February 17, 2022Inventors: Tian Zhou, Djordje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan Kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Publication number: 20220051131Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: ApplicationFiled: August 17, 2020Publication date: February 17, 2022Inventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Gultekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron Flores
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Patent number: 10713692Abstract: Systems, devices, and methods are disclosed for predicting a dynamic floor price for increasing cleared revenue cleared after a winning bid is determined in an online bid auction. The dynamic floor price is predicted from a cascading classifier strategy implemented through a series of cascading machine learning based classifier models that have been trained.Type: GrantFiled: October 13, 2017Date of Patent: July 14, 2020Assignee: Oath Inc.Inventors: Zhihui Xie, Kuang-chih Lee, Junwei Pan